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Evaluating readmission rates and discharge planning by analyzing the length-of-stay of patients

Author

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  • Wanlu Gu

    (University of Arizona)

  • Neng Fan

    (University of Arizona)

  • Haitao Liao

    (University of Arkansas)

Abstract

The length-of-stay (LOS) is an important quality metric in health care, and the use of phase-type (PH) distribution provides a flexible method for modeling LOS. In this paper, we model the patient flow information collected in a hospital for patients of distinct diseases, including headache, liveborn infant, alcohol abuse, acute upper respiratory infection, and secondary cataract. Based on the results obtained from fitting Coxian PH distributions to the LOS data, the patients can be divided into different groups. By analyzing each group to find out their common characteristics, the corresponding readmission rate and other useful information can be evaluated. Furthermore, a comparison of patterns for each disease is analyzed. We conclude that it is important to offering better service and avoiding waste of sources, by the analysis of the relations between groups and readmission. In addition, comparing the patterns within distinct diseases, a better decision for assigning resources and improving the insurance policy can be made.

Suggested Citation

  • Wanlu Gu & Neng Fan & Haitao Liao, 2019. "Evaluating readmission rates and discharge planning by analyzing the length-of-stay of patients," Annals of Operations Research, Springer, vol. 276(1), pages 89-108, May.
    • Handle: RePEc:spr:annopr:v:276:y:2019:i:1:d:10.1007_s10479-018-2957-1
    DOI: 10.1007/s10479-018-2957-1
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    References listed on IDEAS

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    Cited by:

    1. Imran Ali & Devika Kannan, 2022. "Mapping research on healthcare operations and supply chain management: a topic modelling-based literature review," Annals of Operations Research, Springer, vol. 315(1), pages 29-55, August.

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